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The Readiness Score API inspects a domain across five capability areas — discoverability, catalog, checkout, schema, and attribution — and returns a single score and a prioritised list of gaps to fix. Use it to assess a domain before implementation begins, to validate after each implementation step, or to run batch audits across multiple client domains. All calls require authentication — see Authentication.

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Endpoint

POST https://asva-ai.com/api/audit

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Request parameters

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domain
string
required
The domain to audit, without https://. Example: "yourstore.com"
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checks
string[]
Specific checks to run. Omit this field to run all checks.Available values: well_known, catalog, checkout, schema, feed, attribution, entity
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dry_run
boolean
When true, the API returns a cached result without re-fetching the domain. Use this during development to test your integration without triggering a live audit.
What each check tests:
CheckWhat it tests
well_known/.well-known/ucp presence, validity, and accessibility
catalogProduct catalog endpoint structure and data quality
checkoutUCP/ACP checkout endpoint availability
schemaJSON-LD Product, Offer, Organization schema on product pages
feedGoogle Merchant Center feed quality
attributionAsva attribution snippet presence
entityEntity consistency — brand name and organization schema
Example request: 
{
  "domain": "yourstore.com",
  "checks": ["well_known", "catalog", "checkout", "schema", "attribution"],
  "dry_run": false
}

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Response fields

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domain
string
The domain that was audited.
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score
integer
Overall readiness score from 0 to 100. Higher is better.
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grade
string
Letter grade based on the score.
GradeScore range
A80–100
B60–79
C40–59
D0–39
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checked_at
string
ISO 8601 timestamp of when the audit ran.
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gaps
array
Issues found, ordered by severity. Each item in the array contains:
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gaps[].id
string
Unique identifier for this gap type, for example well_known_missing.
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gaps[].check
string
Which check category this gap belongs to.
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gaps[].severity
string
How urgently this gap needs fixing: critical, high, medium, or low.
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gaps[].label
string
Short human-readable description of the gap.
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gaps[].detail
string
Full explanation of the gap and its impact on AI commerce.
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gaps[].fix_url
string
Link to the relevant Asva tool to fix this gap. May be null if no tool applies.
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breakdown
object
Score breakdown by category. Each field is an integer from 0 to 100.
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breakdown.discoverability
integer
Score for agent discoverability — manifest presence and validity.
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breakdown.catalog
integer
Score for product catalog quality and structure.
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breakdown.checkout
integer
Score for checkout endpoint availability and correctness.
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breakdown.attribution
integer
Score for attribution snippet presence and configuration.
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passed
string[]
List of check IDs that passed with no issues.

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Severity reference

SeverityMeaning
criticalBlocks agent discovery or checkout. Fix immediately.
highSignificantly reduces AI traffic or conversion. Fix soon.
mediumAffects attribution or discoverability but not checkout.
lowMinor improvement opportunity.

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Example request and response

curl -X POST https://asva-ai.com/api/audit \
  -H "Authorization: Bearer $ASVA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "domain": "yourstore.com"
  }'
Example response: 
{
  "domain": "yourstore.com",
  "score": 42,
  "grade": "C",
  "checked_at": "2026-04-10T11:00:00Z",
  "gaps": [
    {
      "id": "well_known_missing",
      "check": "well_known",
      "severity": "critical",
      "label": "/.well-known/ucp not found",
      "detail": "No response at https://yourstore.com/.well-known/ucp. Create this file to enable agent discovery.",
      "fix_url": "https://asva-ai.com/tools/manifest"
    },
    {
      "id": "product_schema_incomplete",
      "check": "schema",
      "severity": "high",
      "label": "Product JSON-LD schema missing on 6 pages",
      "detail": "Checked 10 product pages; 6 have no Product or Offer schema. AI systems cannot cite or price these products.",
      "fix_url": null
    },
    {
      "id": "dark_traffic_untracked",
      "check": "attribution",
      "severity": "medium",
      "label": "Asva attribution snippet not detected",
      "detail": "Install the Asva snippet to surface AI-sourced sessions in GA4.",
      "fix_url": "https://asva-ai.com/tools/readiness"
    }
  ],
  "breakdown": {
    "discoverability": 60,
    "catalog": 45,
    "checkout": 30,
    "attribution": 0
  },
  "passed": [
    "https_enabled",
    "feed_exists",
    "merchant_center_connected"
  ]
}

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Batch auditing

For agencies auditing multiple domains, loop through the API: 
#!/bin/bash
domains=("client1.com" "client2.com" "client3.com")

for domain in "${domains[@]}"; do
  result=$(curl -s -X POST https://asva-ai.com/api/audit \
    -H "Authorization: Bearer $ASVA_API_KEY" \
    -H "Content-Type: application/json" \
    -d "{\"domain\": \"$domain\"}")

  score=$(echo $result | jq '.score')
  grade=$(echo $result | jq -r '.grade')
  echo "$domain: $score ($grade)"
done
The /api/audit endpoint allows 60 requests per hour. Space out batch jobs or use dry_run: true for subsequent calls against the same domain within the same session.